// This is an advanced implementation of the algorithm described in the
// following paper:
//   J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time.
//     Robotics: Science and Systems Conference (RSS). Berkeley, CA, July 2014.

// Modifier: Livox               dev@livoxtech.com

// Copyright 2013, Ji Zhang, Carnegie Mellon University
// Further contributions copyright (c) 2016, Southwest Research Institute
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// 1. Redistributions of source code must retain the above copyright notice,
//    this list of conditions and the following disclaimer.
// 2. Redistributions in binary form must reproduce the above copyright notice,
//    this list of conditions and the following disclaimer in the documentation
//    and/or other materials provided with the distribution.
// 3. Neither the name of the copyright holder nor the names of its
//    contributors may be used to endorse or promote products derived from this
//    software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
#include <omp.h>
#include <mutex>
#include <math.h>
#include <thread>
#include <fstream>
#include <csignal>
#include <unistd.h>
#include <Python.h>
#include <so3_math.h>
#include <ros/ros.h>
#include <Eigen/Core>
#include <opencv/cv.h>
#include <common_lib.h>
#include <kd_tree/kd_tree.h>
#include "IMU_Processing.hpp"
#include <nav_msgs/Odometry.h>
#include <nav_msgs/Path.h>
#include <opencv2/core/eigen.hpp>
#include <visualization_msgs/Marker.h>
#include <pcl_conversions/pcl_conversions.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/kdtree/kdtree_flann.h>
#include <pcl/io/pcd_io.h>
#include <sensor_msgs/PointCloud2.h>
#include <tf/transform_datatypes.h>
#include <tf/transform_broadcaster.h>
#include <fast_lio/States.h>
#include <geometry_msgs/Vector3.h>

// #include <Exp_mat.h>


#ifndef DEPLOY
#include "matplotlibcpp.h"
namespace plt = matplotlibcpp;
#endif

#define INIT_TIME           (0)
#define LASER_POINT_COV     (0.0015)
#define NUM_MATCH_POINTS    (5)

std::string root_dir = ROOT_DIR;

int iterCount = 0;
int NUM_MAX_ITERATIONS  = 0;
int FOV_RANGE = 3;  // range of FOV = FOV_RANGE * cube_len
int laserCloudCenWidth  = 24;
int laserCloudCenHeight = 24;
int laserCloudCenDepth  = 24;

int laserCloudValidNum    = 0;
int laserCloudSelNum      = 0;

const int laserCloudWidth  = 48;
const int laserCloudHeight = 48;
const int laserCloudDepth  = 48;
const int laserCloudNum = laserCloudWidth * laserCloudHeight * laserCloudDepth;

std::vector<double> T1, T2, s_plot, s_plot2, s_plot3, s_plot4, s_plot5, s_plot6;

/// IMU relative variables
std::mutex mtx_buffer;
std::condition_variable sig_buffer;
bool lidar_pushed = false;
bool flg_exit = false;
bool flg_reset = false;
bool flg_map_inited = false;

/// Buffers for measurements
double cube_len = 0.0;
double lidar_end_time = 0.0;
double last_timestamp_lidar = -1;
double last_timestamp_imu   = -1;
double HALF_FOV_COS = 0.0;
double res_mean_last = 0.05;
double total_distance = 0.0;
auto   position_last  = Zero3d;
double copy_time, readd_time;

std::deque<sensor_msgs::PointCloud2::ConstPtr> lidar_buffer;
std::deque<sensor_msgs::Imu::ConstPtr> imu_buffer;

//surf feature in map
PointCloudXYZI::Ptr featsFromMap(new PointCloudXYZI());
PointCloudXYZI::Ptr cube_points_add(new PointCloudXYZI());
std::vector<BoxPointType> cub_needrm;
std::vector<BoxPointType> cub_needad;

//all points
PointCloudXYZI::Ptr laserCloudFullRes2(new PointCloudXYZI());
PointCloudXYZI::Ptr featsArray[laserCloudNum];
bool                _last_inFOV[laserCloudNum];
bool                cube_updated[laserCloudNum];
int laserCloudValidInd[laserCloudNum];
pcl::PointCloud<pcl::PointXYZI>::Ptr laserCloudFullResColor(new pcl::PointCloud<pcl::PointXYZI>());

#ifdef USE_ikdtree
KD_TREE ikdtree;
#else
pcl::KdTreeFLANN<PointType>::Ptr kdtreeSurfFromMap(new pcl::KdTreeFLANN<PointType>());
#endif

Eigen::Vector3f XAxisPoint_body(LIDAR_SP_LEN, 0.0, 0.0);
Eigen::Vector3f XAxisPoint_world(LIDAR_SP_LEN, 0.0, 0.0);

//estimator inputs and output;
MeasureGroup Measures;
StatesGroup  state;

void SigHandle(int sig)
{
  flg_exit = true;
  ROS_WARN("catch sig %d", sig);
  sig_buffer.notify_all();
}

//project lidar frame to world
void pointBodyToWorld(PointType const * const pi, PointType * const po)
{
    Eigen::Vector3d p_body(pi->x, pi->y, pi->z);
    Eigen::Vector3d p_global(state.rot_end * (p_body + Lidar_offset_to_IMU) + state.pos_end);
    
    po->x = p_global(0);
    po->y = p_global(1);
    po->z = p_global(2);
    po->intensity = pi->intensity;
}

template<typename T>
void pointBodyToWorld(const Eigen::Matrix<T, 3, 1> &pi, Eigen::Matrix<T, 3, 1> &po)
{
    Eigen::Vector3d p_body(pi[0], pi[1], pi[2]);
    Eigen::Vector3d p_global(state.rot_end * (p_body + Lidar_offset_to_IMU) + state.pos_end);
    po[0] = p_global(0);
    po[1] = p_global(1);
    po[2] = p_global(2);
}

void RGBpointBodyToWorld(PointType const * const pi, pcl::PointXYZI * const po)
{
    Eigen::Vector3d p_body(pi->x, pi->y, pi->z);
    Eigen::Vector3d p_global(state.rot_end * (p_body + Lidar_offset_to_IMU) + state.pos_end);
    
    po->x = p_global(0);
    po->y = p_global(1);
    po->z = p_global(2);
    po->intensity = pi->intensity;

    float intensity = pi->intensity;
    intensity = intensity - std::floor(intensity);

    int reflection_map = intensity*10000;

    // //std::cout<<"DEBUG reflection_map "<<reflection_map<<std::endl;

    // if (reflection_map < 30)
    // {
    //     int green = (reflection_map * 255 / 30);
    //     po->r = 0;
    //     po->g = green & 0xff;
    //     po->b = 0xff;
    // }
    // else if (reflection_map < 90)
    // {
    //     int blue = (((90 - reflection_map) * 255) / 60);
    //     po->r = 0x0;
    //     po->g = 0xff;
    //     po->b = blue & 0xff;
    // }
    // else if (reflection_map < 150)
    // {
    //     int red = ((reflection_map-90) * 255 / 60);
    //     po->r = red & 0xff;
    //     po->g = 0xff;
    //     po->b = 0x0;
    // }
    // else
    // {
    //     int green = (((255-reflection_map) * 255) / (255-150));
    //     po->r = 0xff;
    //     po->g = green & 0xff;
    //     po->b = 0;
    // }
}

int cube_ind(const int &i, const int &j, const int &k)
{
    return (i + laserCloudWidth * j + laserCloudWidth * laserCloudHeight * k);
}

bool CenterinFOV(Eigen::Vector3f cube_p)
{                                
    Eigen::Vector3f dis_vec = state.pos_end.cast<float>() - cube_p;
    float squaredSide1 = dis_vec.transpose() * dis_vec;

    if(squaredSide1 < 0.4 * cube_len * cube_len) return true;

    dis_vec = XAxisPoint_world.cast<float>() - cube_p;
    float squaredSide2 = dis_vec.transpose() * dis_vec;

    float ang_cos = fabs(squaredSide1 <= 3) ? 1.0 :
        (LIDAR_SP_LEN * LIDAR_SP_LEN + squaredSide1 - squaredSide2) / (2 * LIDAR_SP_LEN * sqrt(squaredSide1));
    
    return ((ang_cos > HALF_FOV_COS)? true : false);
}

bool CornerinFOV(Eigen::Vector3f cube_p)
{                                
    Eigen::Vector3f dis_vec = state.pos_end.cast<float>() - cube_p;
    float squaredSide1 = dis_vec.transpose() * dis_vec;

    dis_vec = XAxisPoint_world.cast<float>() - cube_p;
    float squaredSide2 = dis_vec.transpose() * dis_vec;

    float ang_cos = fabs(squaredSide1 <= 3) ? 1.0 :
        (LIDAR_SP_LEN * LIDAR_SP_LEN + squaredSide1 - squaredSide2) / (2 * LIDAR_SP_LEN * sqrt(squaredSide1));
    
    return ((ang_cos > HALF_FOV_COS)? true : false);
}

void lasermap_fov_segment()
{
    laserCloudValidNum = 0;

    pointBodyToWorld(XAxisPoint_body, XAxisPoint_world);

    int centerCubeI = int((state.pos_end(0) + 0.5 * cube_len) / cube_len) + laserCloudCenWidth;
    int centerCubeJ = int((state.pos_end(1) + 0.5 * cube_len) / cube_len) + laserCloudCenHeight;
    int centerCubeK = int((state.pos_end(2) + 0.5 * cube_len) / cube_len) + laserCloudCenDepth;

    if (state.pos_end(0) + 0.5 * cube_len < 0) centerCubeI--;
    if (state.pos_end(1) + 0.5 * cube_len < 0) centerCubeJ--;
    if (state.pos_end(2) + 0.5 * cube_len < 0) centerCubeK--;

    bool last_inFOV_flag = 0;
    int  cube_index = 0;
    cub_needrm.clear();
    cub_needad.clear();
    T2.push_back(Measures.lidar_beg_time);
    double t_begin = omp_get_wtime();

    std::cout<<"centerCubeIJK: "<<centerCubeI<<" "<<centerCubeJ<<" "<<centerCubeK<<std::endl;

    while (centerCubeI < FOV_RANGE + 1)
    {
        for (int j = 0; j < laserCloudHeight; j++)
        {
            for (int k = 0; k < laserCloudDepth; k++)
            {
                int i = laserCloudWidth - 1;

                PointCloudXYZI::Ptr laserCloudCubeSurfPointer = featsArray[cube_ind(i, j, k)];
                last_inFOV_flag = _last_inFOV[cube_index];

                for (; i >= 1; i--) {
                    featsArray[cube_ind(i, j, k)]  = featsArray[cube_ind(i-1, j, k)];
                    _last_inFOV[cube_ind(i, j, k)] = _last_inFOV[cube_ind(i-1, j, k)];
                }

                featsArray[cube_ind(i, j, k)] = laserCloudCubeSurfPointer;
                _last_inFOV[cube_ind(i, j, k)] = last_inFOV_flag;
                laserCloudCubeSurfPointer->clear();
            }
        }
        centerCubeI++;
        laserCloudCenWidth++;
    }

    while (centerCubeI >= laserCloudWidth - (FOV_RANGE + 1)) {
        for (int j = 0; j < laserCloudHeight; j++) {
            for (int k = 0; k < laserCloudDepth; k++) {
                int i = 0;

                PointCloudXYZI::Ptr laserCloudCubeSurfPointer = featsArray[cube_ind(i, j, k)];
                last_inFOV_flag = _last_inFOV[cube_index];

                for (; i >= 1; i--) {
                    featsArray[cube_ind(i, j, k)]  = featsArray[cube_ind(i+1, j, k)];
                    _last_inFOV[cube_ind(i, j, k)] = _last_inFOV[cube_ind(i+1, j, k)];
                }

                featsArray[cube_ind(i, j, k)] = laserCloudCubeSurfPointer;
                _last_inFOV[cube_ind(i, j, k)] = last_inFOV_flag;
                laserCloudCubeSurfPointer->clear();
            }
        }

        centerCubeI--;
        laserCloudCenWidth--;
    }

    while (centerCubeJ < (FOV_RANGE + 1)) {
        for (int i = 0; i < laserCloudWidth; i++) {
            for (int k = 0; k < laserCloudDepth; k++) {
                int j = laserCloudHeight - 1;

                PointCloudXYZI::Ptr laserCloudCubeSurfPointer = featsArray[cube_ind(i, j, k)];
                last_inFOV_flag = _last_inFOV[cube_index];

                for (; i >= 1; i--) {
                    featsArray[cube_ind(i, j, k)]  = featsArray[cube_ind(i, j-1, k)];
                    _last_inFOV[cube_ind(i, j, k)] = _last_inFOV[cube_ind(i, j-1, k)];
                }

                featsArray[cube_ind(i, j, k)] = laserCloudCubeSurfPointer;
                _last_inFOV[cube_ind(i, j, k)] = last_inFOV_flag;
                laserCloudCubeSurfPointer->clear();
            }
        }

        centerCubeJ++;
        laserCloudCenHeight++;
    }

    while (centerCubeJ >= laserCloudHeight - (FOV_RANGE + 1)) {
        for (int i = 0; i < laserCloudWidth; i++) {
            for (int k = 0; k < laserCloudDepth; k++) {
                int j = 0;
                PointCloudXYZI::Ptr laserCloudCubeSurfPointer = featsArray[cube_ind(i, j, k)];
                last_inFOV_flag = _last_inFOV[cube_index];

                for (; i >= 1; i--) {
                    featsArray[cube_ind(i, j, k)]  = featsArray[cube_ind(i, j+1, k)];
                    _last_inFOV[cube_ind(i, j, k)] = _last_inFOV[cube_ind(i, j+1, k)];
                }

                featsArray[cube_ind(i, j, k)] = laserCloudCubeSurfPointer;
                _last_inFOV[cube_ind(i, j, k)] = last_inFOV_flag;
                laserCloudCubeSurfPointer->clear();
            }
        }

        centerCubeJ--;
        laserCloudCenHeight--;
    }

    while (centerCubeK < (FOV_RANGE + 1)) {
        for (int i = 0; i < laserCloudWidth; i++) {
            for (int j = 0; j < laserCloudHeight; j++) {
                int k = laserCloudDepth - 1;
                PointCloudXYZI::Ptr laserCloudCubeSurfPointer = featsArray[cube_ind(i, j, k)];
                last_inFOV_flag = _last_inFOV[cube_index];

                for (; i >= 1; i--) {
                    featsArray[cube_ind(i, j, k)]  = featsArray[cube_ind(i, j, k-1)];
                    _last_inFOV[cube_ind(i, j, k)] = _last_inFOV[cube_ind(i, j, k-1)];
                }

                featsArray[cube_ind(i, j, k)] = laserCloudCubeSurfPointer;
                _last_inFOV[cube_ind(i, j, k)] = last_inFOV_flag;
                laserCloudCubeSurfPointer->clear();
            }
        }

        centerCubeK++;
        laserCloudCenDepth++;
    }

    while (centerCubeK >= laserCloudDepth - (FOV_RANGE + 1))
    {
        for (int i = 0; i < laserCloudWidth; i++)
        {
            for (int j = 0; j < laserCloudHeight; j++)
            {
                int k = 0;
                PointCloudXYZI::Ptr laserCloudCubeSurfPointer = featsArray[cube_ind(i, j, k)];
                last_inFOV_flag = _last_inFOV[cube_index];

                for (; i >= 1; i--) {
                    featsArray[cube_ind(i, j, k)]  = featsArray[cube_ind(i, j, k+1)];
                    _last_inFOV[cube_ind(i, j, k)] = _last_inFOV[cube_ind(i, j, k+1)];
                }

                featsArray[cube_ind(i, j, k)] = laserCloudCubeSurfPointer;
                _last_inFOV[cube_ind(i, j, k)] = last_inFOV_flag;
                laserCloudCubeSurfPointer->clear();
            }
        }

        centerCubeK--;
        laserCloudCenDepth--;
    }

    cube_points_add->clear();
    featsFromMap->clear();
    bool now_inFOV[laserCloudNum] = {false};

    // std::cout<<"centerCubeIJK: "<<centerCubeI<<" "<<centerCubeJ<<" "<<centerCubeK<<std::endl;
    // std::cout<<"laserCloudCen: "<<laserCloudCenWidth<<" "<<laserCloudCenHeight<<" "<<laserCloudCenDepth<<std::endl;

    for (int i = centerCubeI - FOV_RANGE; i <= centerCubeI + FOV_RANGE; i++) 
    {
        for (int j = centerCubeJ - FOV_RANGE; j <= centerCubeJ + FOV_RANGE; j++) 
        {
            for (int k = centerCubeK - FOV_RANGE; k <= centerCubeK + FOV_RANGE; k++) 
            {
                if (i >= 0 && i < laserCloudWidth &&
                        j >= 0 && j < laserCloudHeight &&
                        k >= 0 && k < laserCloudDepth) 
                {
                    Eigen::Vector3f center_p(cube_len * (i - laserCloudCenWidth), \
                                             cube_len * (j - laserCloudCenHeight), \
                                             cube_len * (k - laserCloudCenDepth));

                    float check1, check2;
                    float squaredSide1, squaredSide2;
                    float ang_cos = 1;
                    bool &last_inFOV = _last_inFOV[i + laserCloudWidth * j + laserCloudWidth * laserCloudHeight * k];
                    bool inFOV = CenterinFOV(center_p);

                    for (int ii = -1; (ii <= 1) && (!inFOV); ii += 2) 
                    {
                        for (int jj = -1; (jj <= 1) && (!inFOV); jj += 2) 
                        {
                            for (int kk = -1; (kk <= 1) && (!inFOV); kk += 2) 
                            {
                                Eigen::Vector3f corner_p(cube_len * ii, cube_len * jj, cube_len * kk);
                                corner_p = center_p + 0.5 * corner_p;
                                
                                inFOV = CornerinFOV(corner_p);
                            }
                        }
                    }

                    now_inFOV[i + laserCloudWidth * j + laserCloudWidth * laserCloudHeight * k] = inFOV;

                #ifdef USE_ikdtree
                    /*** readd cubes and points ***/
                    if (inFOV)
                    {
                        int center_index = i + laserCloudWidth * j + laserCloudWidth * laserCloudHeight * k;
                        *cube_points_add += *featsArray[center_index];
                        featsArray[center_index]->clear();
                        if (!last_inFOV)
                        {
                            BoxPointType cub_points;
                            for(int i = 0; i < 3; i++)
                            {
                                cub_points.vertex_max[i] = center_p[i] + 0.5 * cube_len;
                                cub_points.vertex_min[i] = center_p[i] - 0.5 * cube_len;
                            }
                            cub_needad.push_back(cub_points);
                            laserCloudValidInd[laserCloudValidNum] = center_index;
                            laserCloudValidNum ++;
                            // std::cout<<"readd center: "<<center_p.transpose()<<std::endl;
                        }
                    }

                #else
                    if (inFOV)
                    {
                        int center_index = i + laserCloudWidth * j + laserCloudWidth * laserCloudHeight * k;
                        *featsFromMap += *featsArray[center_index];
                        laserCloudValidInd[laserCloudValidNum] = center_index;
                        laserCloudValidNum++;
                    }
                    last_inFOV = inFOV;
                #endif
                }
            }
        }
    }

    #ifdef USE_ikdtree
    /*** delete cubes ***/
    for (int i = 0; i < laserCloudWidth; i++) 
    {
        for (int j = 0; j < laserCloudHeight; j++) 
        {
            for (int k = 0; k < laserCloudDepth; k++) 
            {
                int ind = i + laserCloudWidth * j + laserCloudWidth * laserCloudHeight * k;
                if((!now_inFOV[ind]) && _last_inFOV[ind])
                {
                    BoxPointType cub_points;
                    Eigen::Vector3f center_p(cube_len * (i - laserCloudCenWidth),\
                                             cube_len * (j - laserCloudCenHeight),\
                                             cube_len * (k - laserCloudCenDepth));
                    // std::cout<<"center_p: "<<center_p.transpose()<<std::endl;

                    for(int i = 0; i < 3; i++)
                    {
                        cub_points.vertex_max[i] = center_p[i] + 0.5 * cube_len;
                        cub_points.vertex_min[i] = center_p[i] - 0.5 * cube_len;
                    }
                    cub_needrm.push_back(cub_points);
                }
                _last_inFOV[ind] = now_inFOV[ind];
            }
        }
    }
    #endif

    copy_time = omp_get_wtime() - t_begin;

#ifdef USE_ikdtree
    if(cub_needrm.size() > 0)               ikdtree.Delete_Point_Boxes(cub_needrm);
    // s_plot4.push_back(omp_get_wtime() - t_begin); t_begin = omp_get_wtime();
    if(cub_needad.size() > 0)               ikdtree.Add_Point_Boxes(cub_needad); 
    // s_plot5.push_back(omp_get_wtime() - t_begin); t_begin = omp_get_wtime();
    if(cube_points_add->points.size() > 0)  ikdtree.Add_Points(cube_points_add->points, true);
#endif
    s_plot6.push_back(omp_get_wtime() - t_begin);
    readd_time = omp_get_wtime() - t_begin - copy_time;
}

void feat_points_cbk(const sensor_msgs::PointCloud2::ConstPtr &msg) 
{
    mtx_buffer.lock();
    // std::cout<<"got feature"<<std::endl;
    if (msg->header.stamp.toSec() < last_timestamp_lidar)
    {
        ROS_ERROR("lidar loop back, clear buffer");
        lidar_buffer.clear();
    }

    // ROS_INFO("get point cloud at time: %.6f", msg->header.stamp.toSec());
    lidar_buffer.push_back(msg);
    last_timestamp_lidar = msg->header.stamp.toSec();

    mtx_buffer.unlock();
    sig_buffer.notify_all();
}

void imu_cbk(const sensor_msgs::Imu::ConstPtr &msg_in) 
{
    sensor_msgs::Imu::Ptr msg(new sensor_msgs::Imu(*msg_in));

    double timestamp = msg->header.stamp.toSec();

    mtx_buffer.lock();

    if (timestamp < last_timestamp_imu)
    {
        ROS_ERROR("imu loop back, clear buffer");
        imu_buffer.clear();
        flg_reset = true;
    }

    last_timestamp_imu = timestamp;

    imu_buffer.push_back(msg);
    // std::cout<<"got imu: "<<timestamp<<" imu size "<<imu_buffer.size()<<std::endl;
    mtx_buffer.unlock();
    sig_buffer.notify_all();
}

bool sync_packages(MeasureGroup &meas)
{
    if (lidar_buffer.empty() || imu_buffer.empty()) {
        return false;
    }

    /*** push lidar frame ***/
    if(!lidar_pushed)
    {
        meas.lidar.reset(new PointCloudXYZI());
        pcl::fromROSMsg(*(lidar_buffer.front()), *(meas.lidar));
        meas.lidar_beg_time = lidar_buffer.front()->header.stamp.toSec();
        lidar_end_time = meas.lidar_beg_time + meas.lidar->points.back().curvature / double(1000);
        lidar_pushed = true;
    }

    if (last_timestamp_imu < lidar_end_time)
    {
        return false;
    }

    /*** push imu data, and pop from imu buffer ***/
    double imu_time = imu_buffer.front()->header.stamp.toSec();
    meas.imu.clear();
    while ((!imu_buffer.empty()) && (imu_time < lidar_end_time))
    {
        imu_time = imu_buffer.front()->header.stamp.toSec();
        if(imu_time > lidar_end_time + 0.02) break;
        meas.imu.push_back(imu_buffer.front());
        imu_buffer.pop_front();
    }

    lidar_buffer.pop_front();
    lidar_pushed = false;
    // if (meas.imu.empty()) return false;
    // std::cout<<"[IMU Sycned]: "<<imu_time<<" "<<lidar_end_time<<std::endl;
    return true;
}

int main(int argc, char** argv)
{
    ros::init(argc, argv, "laserMapping");
    ros::NodeHandle nh;

    ros::Subscriber sub_pcl = nh.subscribe("/laser_cloud_flat", 20000, feat_points_cbk);
    ros::Subscriber sub_imu = nh.subscribe("/livox/imu", 20000, imu_cbk);
    ros::Publisher pubLaserCloudFullRes = nh.advertise<sensor_msgs::PointCloud2>
            ("/cloud_registered", 100);
    ros::Publisher pubLaserCloudEffect  = nh.advertise<sensor_msgs::PointCloud2>
            ("/cloud_effected", 100);
    ros::Publisher pubLaserCloudMap = nh.advertise<sensor_msgs::PointCloud2>
            ("/Laser_map", 100);
    ros::Publisher pubOdomAftMapped = nh.advertise<nav_msgs::Odometry> 
            ("/mavros/odometry/out", 10);
    ros::Publisher pubPath          = nh.advertise<nav_msgs::Path> 
            ("/path", 10);
#ifdef DEPLOY
    ros::Publisher mavros_pose_publisher = nh.advertise<geometry_msgs::PoseStamped>("/mavros/vision_pose/pose", 10);
#endif
    geometry_msgs::PoseStamped msg_body_pose;
    nav_msgs::Path path;
    path.header.stamp    = ros::Time::now();
    path.header.frame_id ="/camera_init";

    /*** variables definition ***/
    bool dense_map_en, flg_EKF_inited = 0, flg_map_inited = 0, flg_EKF_converged = 0;
    std::string map_file_path;
    int effect_feat_num = 0, frame_num = 0;
    double filter_size_corner_min, filter_size_surf_min, filter_size_map_min, fov_deg,\
           deltaT, deltaR, aver_time_consu = 0, first_lidar_time = 0;
    Eigen::Matrix<double,DIM_OF_STATES,DIM_OF_STATES> G, H_T_H, I_STATE;
    G.setZero();
    H_T_H.setZero();
    I_STATE.setIdentity();

    nav_msgs::Odometry odomAftMapped;

    cv::Mat matA1(3, 3, CV_32F, cv::Scalar::all(0));
    cv::Mat matD1(1, 3, CV_32F, cv::Scalar::all(0));
    cv::Mat matV1(3, 3, CV_32F, cv::Scalar::all(0));
    cv::Mat matP(6, 6, CV_32F, cv::Scalar::all(0));

    PointType pointOri, pointSel, coeff;
    PointCloudXYZI::Ptr feats_undistort(new PointCloudXYZI());
    PointCloudXYZI::Ptr feats_down(new PointCloudXYZI());
    PointCloudXYZI::Ptr laserCloudOri(new PointCloudXYZI());
    PointCloudXYZI::Ptr coeffSel(new PointCloudXYZI());
    pcl::VoxelGrid<PointType> downSizeFilterSurf;
    pcl::VoxelGrid<PointType> downSizeFilterMap;

    /*** variables initialize ***/
    ros::param::get("~dense_map_enable",dense_map_en);
    ros::param::get("~max_iteration",NUM_MAX_ITERATIONS);
    ros::param::get("~map_file_path",map_file_path);
    ros::param::get("~fov_degree",fov_deg);
    ros::param::get("~filter_size_corner",filter_size_corner_min);
    ros::param::get("~filter_size_surf",filter_size_surf_min);
    ros::param::get("~filter_size_map",filter_size_map_min);
    ros::param::get("~cube_side_length",cube_len);

    HALF_FOV_COS = std::cos((fov_deg + 10.0) * 0.5 * PI_M / 180.0);

    for (int i = 0; i < laserCloudNum; i++)
    {
        featsArray[i].reset(new PointCloudXYZI());
    }

    downSizeFilterSurf.setLeafSize(filter_size_surf_min, filter_size_surf_min, filter_size_surf_min);
    downSizeFilterMap.setLeafSize(filter_size_map_min, filter_size_map_min, filter_size_map_min);

    std::shared_ptr<ImuProcess> p_imu(new ImuProcess());

    /*** debug record ***/
    std::ofstream fout_pre, fout_out;
    fout_pre.open(DEBUG_FILE_DIR("mat_pre.txt"),std::ios::out);
    fout_out.open(DEBUG_FILE_DIR("mat_out.txt"),std::ios::out);
    if (fout_pre && fout_out)
        std::cout << "~~~~"<<ROOT_DIR<<" file opened" << std::endl;
    else
        std::cout << "~~~~"<<ROOT_DIR<<" doesn't exist" << std::endl;

//------------------------------------------------------------------------------------------------------
    signal(SIGINT, SigHandle);
    ros::Rate rate(5000);
    bool status = ros::ok();
    while (status)
    {
        if (flg_exit) break;
        ros::spinOnce();
        while(sync_packages(Measures)) 
        {
            if (flg_reset)
            {
                ROS_WARN("reset when rosbag play back");
                p_imu->Reset();
                flg_reset = false;
                continue;
            }

            double t0,t1,t2,t3,t4,t5,match_start, match_time, solve_start, solve_time, pca_time, svd_time;
            match_time = 0;
            solve_time = 0;
            pca_time   = 0;
            svd_time   = 0;
            t0 = omp_get_wtime();

            p_imu->Process(Measures, state, feats_undistort);
            StatesGroup state_propagat(state);

            if (feats_undistort->empty() || (feats_undistort == NULL))
            {
                first_lidar_time = Measures.lidar_beg_time;
                std::cout<<"not ready for odometry"<<std::endl;
                continue;
            }

            if ((Measures.lidar_beg_time - first_lidar_time) < INIT_TIME)
            {
                flg_EKF_inited = false;
                std::cout<<"||||||||||Initiallizing LiDar||||||||||"<<std::endl;
            }
            else
            {
                flg_EKF_inited = true;
            }
            
            /*** Compute the euler angle ***/
            Eigen::Vector3d euler_cur = RotMtoEuler(state.rot_end);
            fout_pre << std::setw(10) << Measures.lidar_beg_time << " " << euler_cur.transpose()*57.3 << " " << state.pos_end.transpose() << " " << state.vel_end.transpose() \
            <<" "<<state.bias_g.transpose()<<" "<<state.bias_a.transpose()<< std::endl;
            #ifdef DEBUG_PRINT
            std::cout<<"current lidar time "<<Measures.lidar_beg_time<<" "<<"first lidar time "<<first_lidar_time<<std::endl;
            std::cout<<"pre-integrated states: "<<euler_cur.transpose()*57.3<<" "<<state.pos_end.transpose()<<" "<<state.vel_end.transpose()<<" "<<state.bias_g.transpose()<<" "<<state.bias_a.transpose()<<std::endl;
            #endif
            
            /*** Segment the map in lidar FOV ***/
            lasermap_fov_segment();
            
            /*** downsample the features of new frame ***/
            downSizeFilterSurf.setInputCloud(feats_undistort);
            downSizeFilterSurf.filter(*feats_down);

        #ifdef USE_ikdtree
            /*** initialize the map kdtree ***/
            if((feats_down->points.size() > 1) && (ikdtree.Root_Node == nullptr))
            {
                // std::vector<PointType> points_init = feats_down->points;
                ikdtree.set_downsample_param(filter_size_map_min);
                ikdtree.Build(feats_down->points);
                flg_map_inited = true;
                continue;
            }

            if(ikdtree.Root_Node == nullptr)
            {
                flg_map_inited = false;
                std::cout<<"~~~~~~~Initiallize Map iKD-Tree Failed!"<<std::endl;
                continue;
            }
            int featsFromMapNum = ikdtree.size();
        #else
            if(featsFromMap->points.empty())
            {
                downSizeFilterMap.setInputCloud(feats_down);
            }
            else
            {
                downSizeFilterMap.setInputCloud(featsFromMap);
            }
            downSizeFilterMap.filter(*featsFromMap);
            int featsFromMapNum = featsFromMap->points.size();
        #endif
            int feats_down_size = feats_down->points.size();
            std::cout<<"[ mapping ]: Raw feature num: "<<feats_undistort->points.size()<<" downsamp num "<<feats_down_size<<" Map num: "<<featsFromMapNum<<" laserCloudValidNum "<<laserCloudValidNum<<std::endl;

            /*** ICP and iterated Kalman filter update ***/
            PointCloudXYZI::Ptr coeffSel_tmpt (new PointCloudXYZI(*feats_down));
            PointCloudXYZI::Ptr feats_down_updated (new PointCloudXYZI(*feats_down));
            std::vector<double> res_last(feats_down_size, 1000.0); // initial

            if (featsFromMapNum >= 5)
            {
                t1 = omp_get_wtime();
            
            #ifdef USE_ikdtree
                // PointVector ().swap(ikdtree.PCL_Storage);
                // ikdtree.flatten(ikdtree.Root_Node, ikdtree.PCL_Storage);
                // featsFromMap->clear();
                // featsFromMap->points = ikdtree.PCL_Storage;
            #else
                kdtreeSurfFromMap->setInputCloud(featsFromMap);
            #endif

                std::vector<bool> point_selected_surf(feats_down_size, true);
                std::vector<std::vector<int>> pointSearchInd_surf(feats_down_size);
                std::vector<PointVector> Nearest_Points(feats_down_size);
                
                int  rematch_num = 0;
                bool rematch_en = 0;
                flg_EKF_converged = 0;
                deltaR = 0.0;
                deltaT = 0.0;
                t2 = omp_get_wtime();
                
                for (iterCount = 0; iterCount < NUM_MAX_ITERATIONS; iterCount++) 
                {
                    match_start = omp_get_wtime();
                    laserCloudOri->clear();
                    coeffSel->clear();

                    /** closest surface search and residual computation **/
                    omp_set_num_threads(4);
                    #pragma omp parallel for
                    for (int i = 0; i < feats_down_size; i++)
                    {
                        PointType &pointOri_tmpt = feats_down->points[i];
                        PointType &pointSel_tmpt = feats_down_updated->points[i];

                        /* transform to world frame */
                        pointBodyToWorld(&pointOri_tmpt, &pointSel_tmpt);
                        std::vector<float> pointSearchSqDis_surf;
                    #ifdef USE_ikdtree
                        auto &points_near = Nearest_Points[i];
                    #else
                        auto &points_near = pointSearchInd_surf[i];
                    #endif
                        
                        if (iterCount == 0 || rematch_en)
                        {
                            point_selected_surf[i] = true;
                            /** Find the closest surfaces in the map **/
                        #ifdef USE_ikdtree
                            ikdtree.Nearest_Search(pointSel_tmpt, NUM_MATCH_POINTS, points_near, pointSearchSqDis_surf);
                        #else
                            kdtreeSurfFromMap->nearestKSearch(pointSel_tmpt, NUM_MATCH_POINTS, points_near, pointSearchSqDis_surf);
                        #endif
                            float max_distance = pointSearchSqDis_surf[NUM_MATCH_POINTS - 1];
                        
                            if (max_distance > 3)
                            {
                                point_selected_surf[i] = false;
                            }
                        }

                        if (point_selected_surf[i] == false) continue;

                        // match_time += omp_get_wtime() - match_start;

                        double pca_start = omp_get_wtime();

                        /// PCA (using minimum square method)
                        cv::Mat matA0(NUM_MATCH_POINTS, 3, CV_32F, cv::Scalar::all(0));
                        cv::Mat matB0(NUM_MATCH_POINTS, 1, CV_32F, cv::Scalar::all(-1));
                        cv::Mat matX0(NUM_MATCH_POINTS, 1, CV_32F, cv::Scalar::all(0));
                        
                        for (int j = 0; j < NUM_MATCH_POINTS; j++)
                        {
                        #ifdef USE_ikdtree
                            matA0.at<float>(j, 0) = points_near[j].x;
                            matA0.at<float>(j, 1) = points_near[j].y;
                            matA0.at<float>(j, 2) = points_near[j].z;
                        #else
                            matA0.at<float>(j, 0) = featsFromMap->points[points_near[j]].x;
                            matA0.at<float>(j, 1) = featsFromMap->points[points_near[j]].y;
                            matA0.at<float>(j, 2) = featsFromMap->points[points_near[j]].z;
                        #endif
                        }

                        //matA0*matX0=matB0
                        //AX+BY+CZ+D = 0 <=> AX+BY+CZ=-D <=> (A/D)X+(B/D)Y+(C/D)Z = -1
                        //(X,Y,Z)<=>mat_a0
                        //A/D, B/D, C/D <=> mat_x0
            
                        cv::solve(matA0, matB0, matX0, cv::DECOMP_QR);  //TODO

                        float pa = matX0.at<float>(0, 0);
                        float pb = matX0.at<float>(1, 0);
                        float pc = matX0.at<float>(2, 0);
                        float pd = 1;

                        //ps is the norm of the plane norm_vec vector
                        //pd is the distance from point to plane
                        float ps = sqrt(pa * pa + pb * pb + pc * pc);
                        pa /= ps;
                        pb /= ps;
                        pc /= ps;
                        pd /= ps;

                        bool planeValid = true;
                        for (int j = 0; j < NUM_MATCH_POINTS; j++)
                        {
                        #ifdef USE_ikdtree
                            if (fabs(pa * points_near[j].x +
                                        pb * points_near[j].y +
                                        pc * points_near[j].z + pd) > 0.1)
                        #else
                            if (fabs(pa * featsFromMap->points[points_near[j]].x +
                                        pb * featsFromMap->points[points_near[j]].y +
                                        pc * featsFromMap->points[points_near[j]].z + pd) > 0.1)
                        #endif
                            {
                                planeValid = false;
                                point_selected_surf[i] = false;
                                break;
                            }
                        }

                        if (planeValid) 
                        {
                            //loss fuction
                            float pd2 = pa * pointSel_tmpt.x + pb * pointSel_tmpt.y + pc * pointSel_tmpt.z + pd;
                            //if(fabs(pd2) > 0.1) continue;
                            float s = 1 - 0.9 * fabs(pd2) / sqrt(sqrt(pointSel_tmpt.x * pointSel_tmpt.x + pointSel_tmpt.y * pointSel_tmpt.y + pointSel_tmpt.z * pointSel_tmpt.z));

                            if ((s > 0.85))// && ((std::abs(pd2) - res_last[i]) < 3 * res_mean_last))
                            {
                                // if(std::abs(pd2) > 5 * res_mean_last)
                                // {
                                //     point_selected_surf[i] = false;
                                //     res_last[i] = 0.0;
                                //     continue;
                                // }
                                point_selected_surf[i] = true;
                                coeffSel_tmpt->points[i].x = pa;
                                coeffSel_tmpt->points[i].y = pb;
                                coeffSel_tmpt->points[i].z = pc;
                                coeffSel_tmpt->points[i].intensity = pd2;
                                
                                // if(i%50==0) std::cout<<"s: "<<s<<"last res: "<<res_last[i]<<" current res: "<<std::abs(pd2)<<std::endl;
                                res_last[i] = std::abs(pd2);
                            }
                            else
                            {
                                point_selected_surf[i] = false;
                            }
                        }

                        pca_time += omp_get_wtime() - pca_start;
                    }

                    double total_residual = 0.0;
                    laserCloudSelNum = 0;

                    for (int i = 0; i < coeffSel_tmpt->points.size(); i++)
                    {
                        if (point_selected_surf[i] && (res_last[i] <= 2.0))
                        {
                            laserCloudOri->push_back(feats_down->points[i]);
                            coeffSel->push_back(coeffSel_tmpt->points[i]);
                            total_residual += res_last[i];
                            laserCloudSelNum ++;
                        }
                    }

                    res_mean_last = total_residual / laserCloudSelNum;
                    std::cout << "[ mapping ]: Effective feature num: "<<laserCloudSelNum<<" res_mean_last "<<res_mean_last<<std::endl;

                    match_time += omp_get_wtime() - match_start;
                    solve_start = omp_get_wtime();
                    
                    /*** Computation of Measuremnt Jacobian matrix H and measurents vector ***/
                    Eigen::MatrixXd Hsub(laserCloudSelNum, 6);
                    Eigen::VectorXd meas_vec(laserCloudSelNum);
                    Hsub.setZero();

                    // omp_set_num_threads(4);
                    // #pragma omp parallel for
                    for (int i = 0; i < laserCloudSelNum; i++)
                    {
                        const PointType &laser_p  = laserCloudOri->points[i];
                        Eigen::Vector3d point_this(laser_p.x, laser_p.y, laser_p.z);
                        point_this += Lidar_offset_to_IMU;
                        Eigen::Matrix3d point_crossmat;
                        point_crossmat<<SKEW_SYM_MATRX(point_this);

                        /*** get the normal vector of closest surface/corner ***/
                        const PointType &norm_p = coeffSel->points[i];
                        Eigen::Vector3d norm_vec(norm_p.x, norm_p.y, norm_p.z);

                        /*** calculate the Measuremnt Jacobian matrix H ***/
                        Eigen::Vector3d A(point_crossmat * state.rot_end.transpose() * norm_vec);
                        Hsub.row(i) << VEC_FROM_ARRAY(A), norm_p.x, norm_p.y, norm_p.z;

                        /*** Measuremnt: distance to the closest surface/corner ***/
                        meas_vec(i) = - norm_p.intensity;
                    }

                    Eigen::Vector3d rot_add, t_add, v_add, bg_add, ba_add, g_add;
                    Eigen::Matrix<double, DIM_OF_STATES, 1> solution;
                    Eigen::MatrixXd K(DIM_OF_STATES, laserCloudSelNum);
                    
                    /*** Iterative Kalman Filter Update ***/
                    if (!flg_EKF_inited)
                    {
                        /*** only run in initialization period ***/
                        Eigen::MatrixXd H_init(Eigen::Matrix<double, 9, DIM_OF_STATES>::Zero());
                        Eigen::MatrixXd z_init(Eigen::Matrix<double, 9, 1>::Zero());
                        H_init.block<3,3>(0,0)  = Eigen::Matrix3d::Identity();
                        H_init.block<3,3>(3,3)  = Eigen::Matrix3d::Identity();
                        H_init.block<3,3>(6,15) = Eigen::Matrix3d::Identity();
                        z_init.block<3,1>(0,0)  = - Log(state.rot_end);
                        z_init.block<3,1>(0,0)  = - state.pos_end;

                        auto H_init_T = H_init.transpose();
                        auto &&K_init = state.cov * H_init_T * (H_init * state.cov * H_init_T + 0.0001 * Eigen::Matrix<double,9,9>::Identity()).inverse();
                        solution      = K_init * z_init;

                        solution.block<9,1>(0,0).setZero();
                        state += solution;
                        state.cov = (Eigen::MatrixXd::Identity(DIM_OF_STATES, DIM_OF_STATES) - K_init * H_init) * state.cov;
                    }
                    else
                    {
                        auto &&Hsub_T = Hsub.transpose();
                        H_T_H.block<6,6>(0,0) = Hsub_T * Hsub;
                        Eigen::Matrix<double, DIM_OF_STATES, DIM_OF_STATES> &&K_1 = \
                                    (H_T_H + (state.cov / LASER_POINT_COV).inverse()).inverse();
                        K = K_1.block<DIM_OF_STATES,6>(0,0) * Hsub_T;

                        // solution = K * meas_vec;
                        // state += solution;

                        auto vec = state_propagat - state;
                        solution = K * (meas_vec - Hsub * vec.block<6,1>(0,0));
                        state = state_propagat + solution;

                        rot_add = solution.block<3,1>(0,0);
                        t_add   = solution.block<3,1>(3,0);

                        flg_EKF_converged = false;

                        if (((rot_add.norm() * 57.3 - deltaR) < 0.01) \
                           && ((t_add.norm() * 100 - deltaT) < 0.015))
                        {
                            flg_EKF_converged = true;
                        }

                        deltaR = rot_add.norm() * 57.3;
                        deltaT = t_add.norm() * 100;
                    }

                    euler_cur = RotMtoEuler(state.rot_end);

                    #ifdef DEBUG_PRINT
                    std::cout<<"update: R"<<euler_cur.transpose()*57.3<<" p "<<state.pos_end.transpose()<<" v "<<state.vel_end.transpose()<<" bg"<<state.bias_g.transpose()<<" ba"<<state.bias_a.transpose()<<std::endl;
                    std::cout<<"dR & dT: "<<deltaR<<" "<<deltaT<<" res norm:"<<res_mean_last<<std::endl;
                    #endif

                    /*** Rematch Judgement ***/
                    rematch_en = false;
                    if (flg_EKF_converged || ((rematch_num == 0) && (iterCount == (NUM_MAX_ITERATIONS - 2))))
                    {
                        rematch_en = true;
                        rematch_num ++;
                        std::cout<<"rematch_num: "<<rematch_num<<std::endl;
                    }

                    /*** Convergence Judgements and Covariance Update ***/
                    if (rematch_num >= 2 || (iterCount == NUM_MAX_ITERATIONS - 1))
                    {
                        if (flg_EKF_inited)
                        {
                            /*** Covariance Update ***/
                            G.block<DIM_OF_STATES,6>(0,0) = K * Hsub;
                            state.cov = (I_STATE - G) * state.cov;
                            total_distance += (state.pos_end - position_last).norm();
                            position_last = state.pos_end;
                            
                            std::cout<<"position: "<<state.pos_end.transpose()<<" total distance: "<<total_distance<<std::endl;
                        }
                        solve_time += omp_get_wtime() - solve_start;
                        break;
                    }
                    solve_time += omp_get_wtime() - solve_start;
                }
                
                std::cout<<"[ mapping ]: iteration count: "<<iterCount+1<<std::endl;

                t3 = omp_get_wtime();

                /*** add new frame points to map ikdtree ***/
            #ifdef USE_ikdtree
                PointVector points_history;
                ikdtree.acquire_removed_points(points_history);
                
                memset(cube_updated, 0, sizeof(cube_updated));
                
                for (int i = 0; i < points_history.size(); i++)
                {
                    PointType &pointSel = points_history[i];

                    int cubeI = int((pointSel.x + 0.5 * cube_len) / cube_len) + laserCloudCenWidth;
                    int cubeJ = int((pointSel.y + 0.5 * cube_len) / cube_len) + laserCloudCenHeight;
                    int cubeK = int((pointSel.z + 0.5 * cube_len) / cube_len) + laserCloudCenDepth;

                    if (pointSel.x + 0.5 * cube_len < 0) cubeI--;
                    if (pointSel.y + 0.5 * cube_len < 0) cubeJ--;
                    if (pointSel.z + 0.5 * cube_len < 0) cubeK--;

                    if (cubeI >= 0 && cubeI < laserCloudWidth &&
                            cubeJ >= 0 && cubeJ < laserCloudHeight &&
                            cubeK >= 0 && cubeK < laserCloudDepth) 
                    {
                        int cubeInd = cubeI + laserCloudWidth * cubeJ + laserCloudWidth * laserCloudHeight * cubeK;
                        featsArray[cubeInd]->push_back(pointSel);
                        
                    }
                }

                // omp_set_num_threads(4);
                // #pragma omp parallel for
                for (int i = 0; i < feats_down_size; i++)
                {
                    /* transform to world frame */
                    pointBodyToWorld(&(feats_down->points[i]), &(feats_down_updated->points[i]));
                }
                t4 = omp_get_wtime();
                ikdtree.Add_Points(feats_down_updated->points, true);
            #else
                bool cube_updated[laserCloudNum] = {0};
                for (int i = 0; i < feats_down_size; i++)
                {
                    PointType &pointSel = feats_down_updated->points[i];

                    int cubeI = int((pointSel.x + 0.5 * cube_len) / cube_len) + laserCloudCenWidth;
                    int cubeJ = int((pointSel.y + 0.5 * cube_len) / cube_len) + laserCloudCenHeight;
                    int cubeK = int((pointSel.z + 0.5 * cube_len) / cube_len) + laserCloudCenDepth;

                    if (pointSel.x + 0.5 * cube_len < 0) cubeI--;
                    if (pointSel.y + 0.5 * cube_len < 0) cubeJ--;
                    if (pointSel.z + 0.5 * cube_len < 0) cubeK--;

                    if (cubeI >= 0 && cubeI < laserCloudWidth &&
                            cubeJ >= 0 && cubeJ < laserCloudHeight &&
                            cubeK >= 0 && cubeK < laserCloudDepth) {
                        int cubeInd = cubeI + laserCloudWidth * cubeJ + laserCloudWidth * laserCloudHeight * cubeK;
                        featsArray[cubeInd]->push_back(pointSel);
                        cube_updated[cubeInd] = true;
                    }
                }
                for (int i = 0; i < laserCloudValidNum; i++)
                {
                    int ind = laserCloudValidInd[i];

                    if(cube_updated[ind])
                    {
                        downSizeFilterMap.setInputCloud(featsArray[ind]);
                        downSizeFilterMap.filter(*featsArray[ind]);
                    }
                }
            #endif
                t5 = omp_get_wtime();
            }
                
            /******* Publish current frame points in world coordinates:  *******/
            laserCloudFullRes2->clear();
            *laserCloudFullRes2 = dense_map_en ? (*feats_undistort) : (* feats_down);

            int laserCloudFullResNum = laserCloudFullRes2->points.size();
    
            pcl::PointXYZI temp_point;
            laserCloudFullResColor->clear();
            {
            for (int i = 0; i < laserCloudFullResNum; i++)
            {
                RGBpointBodyToWorld(&laserCloudFullRes2->points[i], &temp_point);
                laserCloudFullResColor->push_back(temp_point);
            }

            sensor_msgs::PointCloud2 laserCloudFullRes3;
            pcl::toROSMsg(*laserCloudFullResColor, laserCloudFullRes3);
            laserCloudFullRes3.header.stamp = ros::Time::now();//.fromSec(last_timestamp_lidar);
            laserCloudFullRes3.header.frame_id = "/camera_init";
            pubLaserCloudFullRes.publish(laserCloudFullRes3);
            }

            /******* Publish Effective points *******/
            {
            laserCloudFullResColor->clear();
            pcl::PointXYZI temp_point;
            for (int i = 0; i < laserCloudSelNum; i++)
            {
                RGBpointBodyToWorld(&laserCloudOri->points[i], &temp_point);
                laserCloudFullResColor->push_back(temp_point);
            }
            sensor_msgs::PointCloud2 laserCloudFullRes3;
            pcl::toROSMsg(*laserCloudFullResColor, laserCloudFullRes3);
            laserCloudFullRes3.header.stamp = ros::Time::now();//.fromSec(last_timestamp_lidar);
            laserCloudFullRes3.header.frame_id = "/camera_init";
            pubLaserCloudEffect.publish(laserCloudFullRes3);
            }

            /******* Publish Maps:  *******/
            // sensor_msgs::PointCloud2 laserCloudMap;
            // pcl::toROSMsg(*featsFromMap, laserCloudMap);
            // laserCloudMap.header.stamp = ros::Time::now();//ros::Time().fromSec(last_timestamp_lidar);
            // laserCloudMap.header.frame_id = "/camera_init";
            // pubLaserCloudMap.publish(laserCloudMap);

            /******* Publish Odometry ******/
            // // Transfer to Inertial frame
            // Eigen::Matrix3d R_to_inertial;
            // double G_norm = state.gravity.norm();
            // Eigen::Vector3d G_standard(0,0,-G_norm);
            // Eigen::Vector3d rot_axis = G_standard.cross(state.gravity) / G_norm / G_norm;
            // if(rot_axis.norm()<0.001)
            // {
            //     R_to_inertial = Exp(rot_axis);
            // }
            // else
            // {
            //     Eigen::Vector3d ang_axis = rot_axis / rot_axis.norm();
            //     double ang      = std::asin(rot_axis.norm());
            //     R_to_inertial = Exp(ang_axis, ang);
            // }

            // // Eigen::Vector3d UAV_offset_to_LiD(0.02, 0.02, 0.02);
            // Eigen::Vector3d UAV_offset_to_LiD(-0.05, -0.01, 0.00);
            // // Eigen::Vector3d UAV_offset_to_LiD(-0.00, -0.00, 0.00);
            // Eigen::Vector3d pos_uav = R_to_inertial*(state.pos_end + state.rot_end * UAV_offset_to_LiD);


            // //add transform from camera_init to UAV coordinate 
            // //初始化欧拉角(Z-Y-X，即RPY, 先绕x轴roll,再绕y轴pitch,最后绕z轴yaw)-2.0/180.0*3.1415926
            // Eigen::Vector3d ea(0.0/180.0*3.1415926, 0.0/180.0*3.1415926, 0.00769);
            // Eigen::Vector3d trans_param(0,0,0);//0.03, 0.15, 0.04
 
            // //3.1 欧拉角转换为旋转矩阵
            // Eigen::Matrix3d rotation_matrix3;
            // rotation_matrix3 = Eigen::AngleAxisd(ea[0], Eigen::Vector3d::UnitZ()) * 
            //                    Eigen::AngleAxisd(ea[1], Eigen::Vector3d::UnitY()) * 
            //                    Eigen::AngleAxisd(ea[2], Eigen::Vector3d::UnitX());
            // // cout << "rotation matrix3 =\n" << rotation_matrix3 << endl;   

            // //compute new position
            // Eigen::Vector3d new_trans_pos;
            // new_trans_pos = rotation_matrix3 * state.pos_end + trans_param;

            geometry_msgs::Quaternion geoQuat = tf::createQuaternionMsgFromRollPitchYaw
                    (euler_cur(0), euler_cur(1), euler_cur(2));
            Eigen::Vector3d twist = state.rot_end.transpose() * state.vel_end;


            odomAftMapped.header.frame_id = "odom";//camera_init
            odomAftMapped.child_frame_id = "base_link";
            odomAftMapped.header.stamp = ros::Time::now();//ros::Time().fromSec(last_timestamp_lidar);
            odomAftMapped.pose.pose.orientation.x = geoQuat.x;
            odomAftMapped.pose.pose.orientation.y = geoQuat.y;
            odomAftMapped.pose.pose.orientation.z = geoQuat.z;
            odomAftMapped.pose.pose.orientation.w = geoQuat.w;
            odomAftMapped.pose.pose.position.x = state.pos_end(0);
            odomAftMapped.pose.pose.position.y = state.pos_end(1);
            odomAftMapped.pose.pose.position.z = state.pos_end(2);
            odomAftMapped.twist.twist.linear.x = twist(0);
            odomAftMapped.twist.twist.linear.y = twist(1);
            odomAftMapped.twist.twist.linear.z = twist(2);
            pubOdomAftMapped.publish(odomAftMapped);

            static tf::TransformBroadcaster br;
            tf::Transform                   transform;
            tf::Quaternion                  q;
            transform.setOrigin( tf::Vector3( odomAftMapped.pose.pose.position.x,
                                                odomAftMapped.pose.pose.position.y,
                                                odomAftMapped.pose.pose.position.z ) );
            q.setW( odomAftMapped.pose.pose.orientation.w );
            q.setX( odomAftMapped.pose.pose.orientation.x );
            q.setY( odomAftMapped.pose.pose.orientation.y );
            q.setZ( odomAftMapped.pose.pose.orientation.z );
            transform.setRotation( q );
            br.sendTransform( tf::StampedTransform( transform, odomAftMapped.header.stamp, "/camera_init", "/aft_mapped" ) );

            
            msg_body_pose.header.stamp = ros::Time::now();
            msg_body_pose.header.frame_id = "/camera_odom_frame";
            msg_body_pose.pose.position.x = state.pos_end(0);
            msg_body_pose.pose.position.y = state.pos_end(1);
            msg_body_pose.pose.position.z = state.pos_end(2);
            msg_body_pose.pose.orientation.x = geoQuat.x;
            msg_body_pose.pose.orientation.y = geoQuat.y;
            msg_body_pose.pose.orientation.z = geoQuat.z;
            msg_body_pose.pose.orientation.w = geoQuat.w;
            #ifdef DEPLOY
            mavros_pose_publisher.publish(msg_body_pose);
            #endif

            /******* Publish Path ********/
            msg_body_pose.header.frame_id = "/camera_init";
            path.poses.push_back(msg_body_pose);
            pubPath.publish(path);

            /*** save debug variables ***/
            frame_num ++;
            aver_time_consu = aver_time_consu * (frame_num - 1) / frame_num + (t5 - t0) / frame_num;
            // aver_time_consu = aver_time_consu * 0.8 + (t5 - t0) * 0.2;
            T1.push_back(Measures.lidar_beg_time);
            s_plot.push_back(aver_time_consu);
            s_plot2.push_back(t5 - t3);
            s_plot3.push_back(match_time);
            s_plot4.push_back(float(feats_down_size/10000.0));
            s_plot5.push_back(t5 - t0);

            std::cout<<"[ mapping ]: time: copy map "<<copy_time<<" readd: "<<readd_time<<" match "<<match_time<<" solve "<<solve_time<<"acquire: "<<t4-t3<<" map incre "<<t5-t4<<" total "<<aver_time_consu<<std::endl;
            // fout_out << std::setw(10) << Measures.lidar_beg_time << " " << euler_cur.transpose()*57.3 << " " << state.pos_end.transpose() << " " << state.vel_end.transpose() \
            // <<" "<<state.bias_g.transpose()<<" "<<state.bias_a.transpose()<< std::endl;
            fout_out<<std::setw(8)<<laserCloudSelNum<<" "<<Measures.lidar_beg_time<<" "<<t2-t0<<" "<<match_time<<" "<<t5-t3<<" "<<t5-t0<<std::endl;
        }
        status = ros::ok();
        rate.sleep();
    }
    //--------------------------save map---------------
    // std::string surf_filename(map_file_path + "/surf.pcd");
    // std::string corner_filename(map_file_path + "/corner.pcd");
    // std::string all_points_filename(map_file_path + "/all_points.pcd");

    // PointCloudXYZI surf_points, corner_points;
    // surf_points = *featsFromMap;
    // fout_out.close();
    // fout_pre.close();
    // if (surf_points.size() > 0 && corner_points.size() > 0) 
    // {
    // pcl::PCDWriter pcd_writer;
    // std::cout << "saving...";
    // pcd_writer.writeBinary(surf_filename, surf_points);
    // pcd_writer.writeBinary(corner_filename, corner_points);
    // }

    #ifndef DEPLOY
    if (!T1.empty())
    {
        // plt::named_plot("add new frame",T1,s_plot2);
        // plt::named_plot("search and pca",T1,s_plot3);
        // plt::named_plot("newpoints number",T1,s_plot4);
        plt::named_plot("total time",T1,s_plot5);
        plt::named_plot("average time",T1,s_plot);
        // plt::named_plot("readd",T2,s_plot6);
        plt::legend();
        plt::show();
        plt::pause(0.5);
        plt::close();
    }
    std::cout << "no points saved";
    #endif

    return 0;
}
